Common SNPs explain a large proportion of the heritability for human height.

Prediction error of genetic relationship. The genetic relationship at unobserved causal loci is predicted, with error, from the relationship estimated from genotyped SNPs. The prediction error is calibrated by comparing the relationship at causal loci (mimicked by a set of random SNPs with MAF ≤ θ) to that estimated from another set of random SNPs. Values plotted on y-axis are (1−β) var(Ajk) (see Online Methods for the notations) calculated from different numbers of random SNPs (N) in both adult and adolescent datasets. The slope of each line is equal to 1.0, with R2 = 1.0. The intercept (c) is constant for a certain MAF threshold θ, and c = 6.2 × 10−6 (p-value = 2 × 10−14), 3.4 × 10−6 (p-value = 9 × 10−12), 1.8 × 10−6 (p-value = 4 × 10−10), 7.8 × 10−7 (p-value = 2 × 10−7) and 9.2 × 10−9 (p-value = 0.87, not significant) for θ = 0.1, 0.2, 0.3, 0.4 and 0.5, respectively.

Estimates of variance explained by genome-wide SNPs from adjusted estimates of genetic relationships are unbiased. Results are shown as estimates of variance explained by different proportions of SNPs randomly selected from all the SNPs in the combined set. For each group of SNPs, the variance explained by genome-wide SNPs is estimated using both raw estimates of genetic relationships and adjusted estimates of genetic relationships correcting for prediction error (assuming c = 0). Error bars denote s.e. of the estimate of variance explained by genome-wide SNPs. The log-likelihood ratio test (LRT) statistic is calculated as twice the difference in log-likelihood between the full (h2 ≠ 0) and reduced (h2 = 0) models.

All pairwise comparisons contribute to the estimate of genetic variance. Shown are the squared z-score differences between individuals ( Δyjk2) plotted against the adjusted estimates of genetic relationship ( Ajk∗). The blue line is the linear regression line of Δyjk2 on Ajk∗. The intercept and regression coefficient are estimates of twice the phenotypic variance and minus twice the genetic variances23, respectively. The intercept is 1.98 (s.e. = 0.001) and the regression coefficient is −1.01 (s.e = 0.27), consistent with estimates of the phenotypic and additive genetic variance of 0.990 and 0.505, respectively, and a proportion of variance explained by all SNPs of 0.51.